• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.57-63
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• 2009

Object recognition technologies using PCA(principal component analysis) recognize objects by deciding representative features of objects in the model image, extracting feature vectors from objects in a image and measuring the distance between them and object representation. Given frequent recognition problems associated with the use of point-to-point distance approach, this study adopted the k-nearest neighbor technique(class-to-class) in which a group of object models of the same class is used as recognition unit for the images in-putted on a continual input image. However, the robustness of recognition strategies using PCA depends on several factors, including illumination. When scene constancy is not secured due to varying illumination conditions, the learning performance the feature detector can be compromised, undermining the recognition quality. This paper proposes a new PCA recognition in which database of objects can be detected under different illuminations between input images and the model images.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.905-913
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• 2011

This study was conducted to characterize the discharge feature of pollutant load from the upper and lower watershed influencing on the water quality of South Han River using the empirical equation and Factor Analysis. The results of regression analysis between flow rate and pollutant load were as follows. In the streams of the upper watershed of South Han river, $BOD_5$ and $COD_{Mn}$ were increased as the flow rate was increased. Also, steep increases in SS and TP were observed with positive correlation with the flow rate while change in TN was slightly shown. On the other hand, in the streams of the lower watershed of South Han river, $BOD_5$ was negatively correlated with the flow rate, being decreased with the increase in the flow rate. However, changes in $COD_{Mn}$, TN, SS, and TP showed a similar trend with those observed in the upper watershed. With Factor Analysis of the water quality and various components, it was appeared that the flow rate, SS, and TP were significantly correlated each other and they were indicated as the principal component influencing on water quality in the streams of the upper watershed. In contrast, $BOD_5$, $COD_{Mn}$ and TOC were significantly correlated each other and they were included as the principal pollution component of the streams in the lower watershed. From these results, it was conclusive that the upper watershed of South Han River was mainly affected by non point source pollutants while the lower watershed was influenced by point source pollutants from the developed areas.

• Journal of Korean Society on Water Environment
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• v.37 no.6
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• pp.520-530
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• 2021

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (BOD) shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.329-334
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• 2017

This paper discusses the near field characteristics of a dipole source located near conducting metallic walls from an electromagnetic compatibility (EMC) point of view. An integral equation for a dipole source near a metallic wall is derived and solved by applying Galerkin's method of moments (MoM). The results show that in the regions outside the dipole source, total electric near fields decrease gradually in magnitude with an increasing field point from the dipole source. But in the regions inside the dipole source, total electric near fields decrease rapidly with a dipole position of $h{\leq}0.3{\lambda}$. For a dipole position of $h{\geq}0.7{\lambda}$, the peaks and nulls of the total near electric field occur periodically in the regions inside the dipole source, and the fluctuation period is almost $0.5{\lambda}$. The worst position for a receptor location is along the z-axis, and a range of a half-magnitude of the maximum near electric field in the principal H-plane is about two times broader than that of the principal E-plane. Experimental measurements are also presented to validate the theory.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.506-516
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• 1998

In this paper, an algorithm is proposed to detect the malfunction of plasma-etching characteristics using EPD signal trajectories. EPD signal trajectories offer many information on plasma-etching process state, so they must be considered as the most important data sets to predict the wafer states in plasma-etching process. A recent work has shown that EPD signal trajectories were successfully incorporated into process modeling through critical parameter extraction, but this method consumes much effort and time. So Principal component analysis(PCA) can be applied. PCA is the linear transformation algorithm which converts correlated high-dimensional data sets to uncorrelated low-dimensional data sets. Based on this reason neural network model can improve its performance and convergence speed when it uses the features which are extracted from raw EPD signals by PCA. Wafer-state variables, Critical Dimension(CD) and uniformity can be estimated by simulation using neural network model into which EPD signals are incorporated. After CD and uniformity values are predicted, proposed algorithm determines whether malfunction values are produced or not. If malfunction values arise, the etching process is stopped immediately. As a result, through simulation, we can keep the abnormal state of etching process from propagating into the next run. All the procedures of this algorithm can be performed on-line, i.e. wafer to wafer.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2313-2318
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• 2000

The method of photoelasticity allows one to obtain principal stress differences and principal stress directions in a photoelastic model. In the classical approach, the photoelastic parameters are measured manually point by point. This is time consuming and requires skill in the identification and measurement of photoelastic data. Fringe phase shifting method has been recently developed and widely used to measure and analyze fringe data in photo-mechanics. This paper presents the test results of photoelastic fringe phase shifting method for the stress analysis of a curved beam plate. The technique used here requires four phase stepped photoelastic images obtained from a circular polariscope by rotating the analyzer at 0˚, 45˚, 90˚ and 135˚. Experimental results are compared with those of ANSYS and calculated by the simple beam theory. Good agreement among the results can be observed.

• Journal of the Korean Vacuum Society
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• v.15 no.4
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• pp.338-346
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• 2006

In semiconductor process, it is so hard to predict an exact failure point of the vacuum pump due to its harsh operation conditions and nonlinear properties, which may causes many problems, such as production of inferior goods or waste of unnecessary materials. Therefore it is very urgent and serious problem to develop diagnostic models which can monitor the operation conditions appropriately and recognize the failure point exactly, indicating when to replace the vacuum pump. In this study, many influencing factors are totally considered and eventually the monitoring model using multivariate statistical methods is suggested. The pivotal algorithms are Multiway Principal Component Analysis(MPCA), Dynamic Time Warping Algorithm(DTW Algorithm), etc.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.32 no.1
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• pp.52-59
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• 2006

Purpose: The purpose of this study was to evaluate the influence of apical-coronal implant position on the stress distribution after occlusal and oblique loading. Materials and Methods: The cortical and cancellous bone was assumed to be isotropic, homogeneous, and linearly elastic. The implant was apposed to cortical bone in the crestal region and to cancellous bone for the remainder of the implant-bone interface. The cancellous core was surrounded by 2-mm-thick cortical bone. An axial load of 200 N was assumed and a 200-N oblique load was applied at a buccal inclination of 30 degrees to the center of the pontic and buccal cusps. The 3-D geometry modeled in Iron CAD was interfaced with ANSYS. Results: When only the stress in the bone was compared, the minimal principal stress at load Points A and B, with a axial load applied at 90 degrees or an oblique load applied at 30 degrees, for model 5. The von Mises stress in the screw of model 5 was minimal at Points A and B, for 90- and 30-degree loads. When the von Mises stress of the abutment screw was compared at Points A and B, and a 30-degree oblique load, the maximum principal stress was seen with model 2, while the minimum principal stress was with model 5. In the case of implant, the model that received maximum von Mises stress was model 1 with the load Point A and Point B, axial load applied in 90-degree, and oblique load applied in 30-degree. Discussion and Conclusions: These results suggests that implantation should be done at the supracrestal level only when necessary, since it results in higher stress than when implantation is done at or below the alveolar bone level. Within the limited this study, we recommend the use of supracrestal apical-coronal positioning in the case of clinical indications.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.61-74
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• 2020

Interval-valued data, one type of symbolic data, are observed in the form of intervals rather than single values. Each interval-valued observation has an internal variation. Principal component analysis reduces the dimension of data by maximizing the variance of data. Therefore, the principal component analysis of the interval-valued data should account for the variance between observations as well as the variation within the observed intervals. In this paper, three principal component analysis methods for interval-valued data are summarized. In addition, a new method using a truncated normal distribution has been proposed instead of a uniform distribution in the conventional quantile method, because we believe think there is more information near the center point of the interval. Each method is compared using simulations and the relevant data set from the OECD. In the case of the quantile method, we draw a scatter plot of the principal component, and then identify the position and distribution of the quantiles by the arrow line representation method.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.575-578
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• 2007

The objective of this study is to analyze the regionalization of point rainfall by statistical methods for regional frequency analysis of the rainfall. The rainfall data used in this study are annual maximum rainfall at 57 stations during the period of more than 30 years for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr) in Korea. The Mann-Whitney U test, Kruskal-Wallis one-way analysis of variance of nonparametric test the principal component and the cluster analysis have been performed to analyze the regionalization of rainfall. The results of this study are as follows; (1) The region which hydrological homogeneous is accepted does not exist for whole duration in Korea. (2) The result of nonpametric test shows that hydrological homogeneous regions of point rainfall are divided by 5 regions. (3) In case of cluster analysis hydrological homogeneous regions of point rainfall are divided by 6 regions and 4 other areas.